TY - GEN
T1 - Targeted vaccination based on a wireless sensor system
AU - Sun, Xiao
AU - Lu, Zongqing
AU - Zhang, Xiaomei
AU - Salathe, Marcel
AU - Cao, Guohong
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - Vaccination is one of the most effective ways to protect people from being infected by infectious disease. However, it is often impractical to vaccinate all people in a community due to various resource constraints. Therefore, targeted vaccination, which vaccinates a small group of people, is an alternative approach to contain infectious disease spread. To achieve better performance in targeted vaccination, we collect student contact traces in a high school based on wireless sensors carried by students. With our wireless sensor system, we can record student contacts within the disease propagation distance, and then construct a disease propagation graph to model the infectious disease propagation. Based on this graph, we propose a metric called connectivity centrality to measure a node's importance during disease propagation and design centrality based algorithms for targeted vaccination. The proposed algorithms are evaluated and compared with other schemes based on our collected traces. Trace driven simulation results show that our algorithms can help to effectively contain infectious disease.
AB - Vaccination is one of the most effective ways to protect people from being infected by infectious disease. However, it is often impractical to vaccinate all people in a community due to various resource constraints. Therefore, targeted vaccination, which vaccinates a small group of people, is an alternative approach to contain infectious disease spread. To achieve better performance in targeted vaccination, we collect student contact traces in a high school based on wireless sensors carried by students. With our wireless sensor system, we can record student contacts within the disease propagation distance, and then construct a disease propagation graph to model the infectious disease propagation. Based on this graph, we propose a metric called connectivity centrality to measure a node's importance during disease propagation and design centrality based algorithms for targeted vaccination. The proposed algorithms are evaluated and compared with other schemes based on our collected traces. Trace driven simulation results show that our algorithms can help to effectively contain infectious disease.
UR - http://www.scopus.com/inward/record.url?scp=84942571078&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84942571078&partnerID=8YFLogxK
U2 - 10.1109/PERCOM.2015.7146531
DO - 10.1109/PERCOM.2015.7146531
M3 - Conference contribution
AN - SCOPUS:84942571078
T3 - 2015 IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
SP - 215
EP - 220
BT - 2015 IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Pervasive Computing and Communications, PerCom 2015
Y2 - 23 March 2015 through 27 March 2015
ER -
